Mid/Senior MLOps Engineer

Want to lead the culture of data-driven decision-making? Love turning data into meaningful, actionable insights? If so, we want you on our Data team! This team comprises experts who specialize in collecting, analyzing, and interpreting large amounts of data, as well as building predictive models using machine learning algorithms. The Data team also takes pride in creating robust ETLs and dashboards that allow other teams to monitor, plan, and achieve their goals effectively. 
As an MLOps Engineer, you will play a crucial role in architecting, implementing, and maintaining the core infrastructure that supports our data ecosystem, including machine learning pipelines. If this sounds appealing, read along!

If you want to:

• Develop, design, and maintain the entire end-to-end machine learning life cycle, ensuring seamless integration with the enterprise ecosystem;
• Collaborate with data scientists and engineers to optimize the ML pipeline’s performance, including preprocessing, feature engineering, training, and evaluation;
• Turn ML algorithms into scalable, production-ready solutions;
• Troubleshoot and debug ML model deployment and integration issues, ensuring smooth production operation;
• Monitor and evaluate the performance of ML models in production, making necessary adjustments to maintain accuracy and reliability;
• Design and implement continuous training processes for ML models, ensuring they stay up-to-date with evolving data and business requirements;
• Establish and configure CI/CD/CT processes specifically tailored for ML workflows;
• Explore and introduce new ML tools to boost team efficiency.

And you can check off:

• Solid background in Machine Learning.
• Skills in building highly available and scalable ML-driven applications and systems;
• Excellent Python development skills;
• Familiarity with experiment tracking, ML models, and data versioning platforms (GCP Vertex AI, MLflow, Feature stores, etc.);
• Experience working with Cloud Service Providers (GCP, AWS), packaging, and IaC tools (Docker, Terraform);
• Knowledge of version control systems and CI/CD practices in the context of ML development, deployment, and process automation;
• Understanding of data engineering and data pipeline concepts;
• Deep knowledge of MLOps concepts and best practices;

Here’s the deal:

• Growth and learning opportunities: time dedicated to learning, conferences, online learning platforms, and books for your professional development;
• Health and wellness: We want you to feel and be your best. That's why we offer various benefits, from online workouts and a physical coach to health insurance and regular mental health checks;
• Tools of your choice: choose the technical equipment and tools you need to do your best work;
• Community and celebrations: get ready for long-lasting traditions such as yearly workation, Friday get-togethers, various team buildings, and company celebrations;
• Work-life balance: We encourage working in the office, with the possibility of up to two remote days per week. Plus, with our WFA policy, you can work from almost anywhere in the world;
• More days off: additional vacation days depending on your tenure;
• Premium Surfshark accounts: for you, your family, and friends;
• Gross salary: 3400 - 7100 EUR/month. Although it may vary depending on your skills and experience.